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Retinal screening contributes to early detection of diabetic retinopathy and timely treatment. To facilitate the screening process, we develop a deep learning system, named DeepDR, that can detect early-to-late stages of diabetic retinopathy. DeepDR is trained for real-time image quality assessment, lesion detection and grading using 466,247 fundus images from 121,342 patients with diabetes. Evaluation is performed on a local dataset with 200,136 fundus images from 52,004 patients and three external datasets with a total of 209,322 images. The area under the receiver operating characteristic curves for detecting microaneurysms, cotton-wool spots, hard exudates and hemorrhages are 0.901, 0.941, 0.954 and 0.967, respectively. The grading of diabetic retinopathy as mild, moderate, severe and proliferative achieves area under the curves of 0.943, 0.955, 0.960 and 0.972, respectively. In external validations, the area under the curves for grading range from 0.916 to 0.970, which further supports the system is efficient for diabetic retinopathy grading. As the leading cause of vision loss in working-age adults, diabetic retinopathy requires routinely retinal screening. Here the authors develop a deep learning system that can facilitate the screening by providing real-time image quality assessment, lesions detection, and grades across the disease spectrum.

Diabetic Retinopathy (DR) is one of the most important microvascular complications of diabetes mellitus, which can lead to blindness in severe cases. Mitochondria are energy-producing organelles in eukaryotic cells, which participate in metabolism and signal transduction, and regulate cell growth, differentiation, aging, and death. Metabolic changes of retinal cells and epigenetic changes of mitochondria-related genes under high glucose can lead to mitochondrial dysfunction and induce mitochondrial pathway apoptosis. In addition, mitophagy and mitochondrial dynamics also change adaptively. These mechanisms may be related to the occurrence and progression of DR, and also provide valuable clues for the prevention and treatment of DR. This article reviews the mechanism of DR induced by mitochondrial dysfunction, and the prospects for related treatment.

PurposeTo develop age-specific and gender-specific reference percentile charts for axial length (AL) and AL/corneal radius of curvature (AL/CR) and, to use percentiles to determine probability of myopia and estimate refractive error (RE).MethodsAnalysis of AL, cycloplegic RE and CR of 14 127 Chinese participants aged 4–18 years from 3 studies. AL and AL/CR percentiles estimated using Lambda-Mu-Sigma method and compared for agreement using intraclass correlation (ICC). Logistic regression was used to model risk of myopia based on age, gender, AL and AL/CR percentiles. Accuracy of AL progression and RE estimated using percentiles was validated using an independent sample of 5742 eyes of children aged 7–10 years.ResultsAge-specific and gender-specific AL and AL/CR (3rd, 5th, 10th, 25th, 50th, 75th, 90th and 95th) percentiles are presented. Concordance between AL and AL/CR percentiles improved with age (0.13 at 4 years to >0.75 from 13 years) and a year-to-year change was observed for all except <10th percentile from 15 years. Increasing age, AL and AL/CR was associated with a more myopic RE (r2=0.45,0.70 and 0.83, respectively). The sensitivity and specificity of the model to estimate probability of myopia was 86.0% and 84.5%, respectively. Estimation of 1-year change in AL using percentiles correlated highly with actual AL (ICC=0.98). Concordance of estimated to actual RE was high (ICC=0.80) and within ±0.50D and ±1.0D of actual RE for 47.4% and 78.9% of eyes, respectively.ConclusionAge-specific and gender-specific AL and AL/CR percentiles provide reference data, aid in identifying and monitoring individuals at risk of myopia and have utility in screening for myopia. AL/CR percentiles were more accurate in estimating probability of myopia in younger children.

Diabetes mellitus (DM) is a complex metabolic syndrome characterized by hyperglycemia. Diabetic retinopathy (DR) is the most common complication of DM and the leading cause of blindness in the working-age population of the Western world. Lipopolysaccharides (LPS) is an essential ingredient of the outer membrane of gram-negative bacteria, which induces systemic inflammatory responses and cellular apoptotic changes in the host. High-level serum LPS has been found in diabetic patients at the advanced stages, which is mainly due to gut leakage and dysbiosis. In this light, increasing evidence points to a strong correlation between systemic LPS challenge and the progression of DR. Although the underlying molecular mechanisms have not been fully elucidated yet, LPS-related pathobiological events in the retina may contribute to the exacerbation of vasculopathy and neurodegeneration in DR. In this review, we focus on the involvement of LPS in the progression of DR, with emphasis on the blood-retina barrier dysfunction and dysregulated glial activation. Eventually, we summarize the recent advances in the therapeutic strategies for antagonising LPS activity, which may be introduced to DR treatment with promising clinical value.

Diabetic retinopathy (DR) is an important cause of blindness globally, and its prevalence is increasing. Early detection and intervention can help change the outcomes of the disease. The rapid development of artificial intelligence (AI) in recent years has led to new possibilities for the screening and diagnosis of DR. An AI-based diagnostic system for the detection of DR has significant advantages, such as high efficiency, high accuracy, and lower demand for human resources. At the same time, there are shortcomings, such as the lack of standards for development and evaluation and the limited scope of application. This article demonstrates the current applications of AI in the field of DR, existing problems, and possible future development directions.

PurposeThis study aimed to explore the characteristics of retinal perfusion and its associations with high myopia.MethodsA total of 760 participants were included. Peripapillary radial peripapillary capillary perfusion, foveal avascular zone, and parafoveal perfusion were measured using optical coherence tomography angiography (OCTA). Tilted disc ratio and parapapillary atrophy were determined using swept-source optical coherence tomography.ResultsA total of 760 young healthy participants with myopic eyes were included in the analysis. The mean axial length and titled disc ratio were 26.43 ± 1.14 and 0.76 ± 0.08 mm in the high-myopia group and 24.79 ± 0.75 and 0.80 ± 0.09 mm in the control group, respectively. The high-myopia group exhibited significantly larger parapapillary atrophy, lower tilted disc ratio, lower radial peripapillary capillary vessel density, larger area of foveal avascular zone, and lower deep parafoveal vessel density. In the multivariate analysis, titled disc ratio significantly correlated with radial peripapillary capillary vessel density (P = 0.0134), larger foveal avascular zone (P = 0.0062), and lower deep parafoveal vessel density (P < 0.0001).ConclusionsReduced radial peripapillary capillary and deep parafoveal vessel density and enlarged area of foveal avascular zone were observed in high myopia. Tilted disc ratio correlated with retinal perfusion.

IntroductionPathologic myopia (PM) is a leading cause of irreversible blindness worldwide, yet effective therapeutic interventions remain limited. Although repeated low-level red light (RLRL) therapy has demonstrated significant efficacy in controlling myopia progression among children, its application in patients with PM remains unexplored. This study aims to evaluate the regulatory effects of RLRL on choroidal vascular density and thickness in patients with PM and verify its safety and efficacy in delaying the progression of fundus atrophic lesions.Methods and analysisThis is a prospective, randomised, controlled trial enrolling 158 patients with PM aged 18–55 years. Participants will be randomised (1:1) to an intervention group or a control group. The intervention group will receive light-emitting diode–based RLRL therapy (wavelength, 660 nm; power density, 65 mW/cm²) administered two times daily for 3 min per session, 5 days per week, over a 12-month period. The control group will receive a sham treatment (power density, 5 mW/cm²) following an identical schedule. The primary outcome measure is the change in choroidal vascular density and choroidal vessel volume index at 12 months.Ethics and disseminationThis study has been approved by the Ethics Review Committee of Shanghai Eye Disease Prevention and Treatment Centre (EC-20250506-04). This study will be conducted in adherence to the approved protocol, Good Clinical Practice and the Declaration of Helsinki. The study results will be submitted to a peer-reviewed journal and presented at both local and international congresses.Trial registration numberNCT07312214

To evaluate the association between the AL/CR ratio and refractive state and explore the effectiveness of this ratio in the assessment of myopia, especially when combined with uncorrected visual acuity in schoolchildren among whom myopia is common. Cross sectional study. 4686 children from 6 primary schools, aged from 6 to 12 years were selected using the clustered-stratified random sampling method. Uncorrected visual acuity (UCVA), axial length (AL), corneal radius of curvature (CR), and cycloplegic refraction were tested. Refraction was measured as the spherical equivalent (SE). 3922 children were included in the analysis. The mean AL/CR ratio was 2.973±0.002, increased with age, and different in gender. The coefficients of correlations of the SE with the AL/CR ratio, AL, and CR were -0.811, -0.657, and 0.095, respectively. Linear regression showed a 10.72 D shift towards myopia with every 1 unit increase in the AL/CR ratio (P<0.001, r2 = 66.4%). The estimated SE values obtained by substituting the AL/CR ratio and gender back to the regression model that were within a difference of ±0.50 D in ATE/LER (allowable total error and limits for erroneous results) zones compared to the actual measured values was 51%. The area under the ROC curve of the AL/CR ratio, AL, and UCVA for myopia detection were 0.910, 0.822, and 0.889, respectively, and the differences between each pair were statistically significant (P<0.01). At a specificity of 90%, the sensitivities were 72.98%, 50.50%, 71.99%, and 82.96%, respectively, for the AL/CR ratio, AL, UCVA, and the combination of the AL/CR ratio and UCVA. The AL/CR ratio was found to explain the total variance in SE better than AL alone. The effectiveness of the AL/CR ratio was statistically significantly better than UCVA for detecting myopia in children, and combining the two produced increased sensitivity without significantly decreasing specificity.

Background There is increasing evidence that exposure to PM 2.5 and its constituents is associated with an increased risk of gestational diabetes mellitus (GDM), but studies on the relationship between exposure to PM 2.5 constituents and the risk of GDM are still limited. Methods A total of 17,855 pregnant women in Guangzhou were recruited for this retrospective cohort study, and the time-varying average concentration method was used to estimate individual exposure to PM 2.5 and its constituents during pregnancy. Logistic regression was used to assess the relationship between exposure to PM 2.5 and its constituents and the risk of GDM, and the expected inflection point between exposure to PM 2.5 and its constituents and the risk of GDM was estimated using logistic regression combined with restricted cubic spline curves. Stratified analyses and interaction tests were performed. Results After adjustment for confounders, exposure to PM 2.5 and its constituents (NO 3 − , NH 4 + , and OM) was positively associated with the risk of GDM during pregnancy, especially when exposure to NO 3 − and NH 4 + occurred in the first to second trimester, with each interquartile range increase the risk of GDM by 20.2% (95% CI: 1.118–1.293) and 18.2% (95% CI. 1.107–1.263), respectively. The lowest inflection points between PM 2.5 , SO 4 2− , NO 3 − , NH 4 + , OM, and BC concentrations and GDM risk throughout the gestation period were 18.96, 5.80, 3.22, 2.67, 4.77 and 0.97 µg/m 3 , respectively. In the first trimester, an age interaction effect between exposure to SO 4 2− , OM, and BC and the risk of GDM was observed. Conclusions This study demonstrates a positive association between exposure to PM 2.5 and its constituents and the risk of GDM. Specifically, exposure to NO 3 − , NH 4 + , and OM was particularly associated with an increased risk of GDM. The present study contributes to a better understanding of the effects of exposure to PM 2.5 and its constituents on the risk of GDM.

Myopia is a significant global health concern and affects human visual function, resulting in blurred vision at a distance. There are still many unsolved challenges in this field that require the help of new technologies. Currently, artificial intelligence (AI) technology is dominating medical image and data analysis and has been introduced to address challenges in the clinical practice of many ocular diseases. AI research in myopia is still in its early stages. Understanding the strengths and limitations of each AI method in specific tasks of myopia could be of great value and might help us to choose appropriate approaches for different tasks. This article reviews and elaborates on the technical details of AI methods applied for myopia risk prediction, screening and diagnosis, pathogenesis, and treatment.